The observation data obtained by performing sensing with the use of the sensing equipment such as a radar is used for estimation of the position and the shape of an object which is located around the sensing equipment, mobility/stationarity (a moving object or a stationary object) of the object and so forth. The observation data includes many uncertain elements such as an observation error or disturbances. Accordingly, it may be necessary to perform some sort of a filtering process in order to obtain accurate information on an object to be observed.
Many of existing techniques for perceiving and estimating the surrounding objects from the observation data obtained by using the sensing equipment are based on stochastic methods. As one of such stochastic methods, there exists a method which has been firstly proposed by Non-Patent Document 1 described below and has used an Occupancy Grid Map. In the following, a method of using the occupancy grid map which has been proposed again in Non-Patent Document 2 described below will be briefly described on the basis of the method which has been firstly proposed by Non-Patent Document 1.
The method of using the occupancy grid map includes the following steps: preparing the occupancy grid map that a surrounding space to be observed is partitioned into grids; and calculating an occupation probability p(m) which indicates whether each of the grids is in an occupied state (the occupied state is designated by “m”) or in an unoccupied state, that is, whether a space in that grid is physically filled. FIG. 1 shows one example of the occupancy grid map of related art.
When an observation has been performed in a t time-frame (a time t), the probability as to whether the grid (each area which is partitioned in the form of grid in FIG. 1) which corresponds to the space sensed by a sensor is occupied or unoccupied is calculated and updated. According to the technique proposed in Non-Patent Document 2, an updating formula of the occupation probability p(m) is expressed by the following formula (1) for a certain grid i and a state in the t time frame (the time t) is derived from a state in a t−1 time frame (a time t−1) by the numerical formula (1).
                    [                  Numerical          ⁢                                          ⁢          Formula          ⁢                                          ⁢          1                ]                                                                      log          ⁢                                    p              ⁡                              (                                                                            m                      i                                        ❘                                          z                      1                                                        ,                  …                  ⁢                                                                          ,                                      z                    t                                                  )                                                    1              -                              p                ⁡                                  (                                                                                    m                        i                                            ❘                                              z                        1                                                              ,                    …                    ⁢                                                                                  ,                                          z                      t                                                        )                                                                    =                              log            ⁢                                          p                ⁡                                  (                                                            m                      i                                        ❘                                          z                      t                                                        )                                                            1                -                                  p                  ⁡                                      (                                                                  m                        i                                            ❘                                              z                        t                                                              )                                                                                +                      log            ⁢                                          1                -                                  p                  ⁡                                      (                                          m                      i                                        )                                                                              p                ⁡                                  (                                      m                    i                                    )                                                              +                      log            ⁢                                          p                ⁡                                  (                                                                                    m                        i                                            ❘                                              z                        1                                                              ,                    …                    ⁢                                                                                  ,                                          z                                              t                        -                        1                                                                              )                                                            1                -                                  p                  ⁡                                      (                                                                                            m                          i                                                ❘                                                  z                          1                                                                    ,                      …                      ⁢                                                                                          ,                                              z                                                  t                          -                          1                                                                                      )                                                                                                          (        1        )            
In the formula (1), additions are performed for the occupation probability p(m) by using a logarithm (LogOdds) of a value that the occupation probability p(m) has been divided by a non-occupation probability 1−p(m) as a unit.
The left side of the formula (1) is logarithmic odds of an occupation probability p(mi|z1, . . . , zt) which has been obtained up to the t time frame (the time t) and indicates the latest estimation result of the occupation probability p(m) in the grid i. The left side (that is, the latest estimation result of the occupation probability p(m)) of the formula (1) is obtained by calculating the right side of the formula (1). The left side of the formula (1) is called a logarithm-likelihood ratio in the observation performed up to the time t.
The right-side first term of the formula (1) is logarithmic odds of an occupation probability p(mi|zt) of an observation intensity zt of the t time frame (the time t) in the grid i. A result of observation performed in the t time frame (the time t) in the grid i which has been obtained by the sensor is substituted into the right-side first term. The right-side first term of the formula (1) is called a logarithm-likelihood ratio in observation performed at the time t.
The right-side second term of the formula (1) indicates an initial value and is logarithmic odds of an occupation probability p(mi) which has been set as the initial value in the grid i. The occupation probability p(mi) in an initial state where no observation is performed may be set to, for example, p(mi)=0.5.
The right-side third term of the formula (1) is logarithmic odds of an occupation probability p(mi|z1, . . . , zt-1) which has been obtained up to a t−1 time frame (a time t−1) in the grid i and a value of a result of estimation (the left side of the formula (1) which has been obtained by a calculation performed directly before the estimation) which has been obtained in the calculation performed directly before the estimation is substituted into the right-side third term. The right-side third term of the formula (1) is called a logarithm-likelihood ratio in observation performed up to the time t−1.
When the occupation probability p(mi) in the initial state has been set to p(mi)=0.5 as mentioned above, also the non-occupation probability 1−p(mi) is set to 1−p(mi)=0.5 and therefore the right-side second term of the formula (1) is set to zero. That is, when p(mi)=0.5 has been set as the initial value, the value of the logarithm-likelihood ratio in the observation performed up to the time t is obtained by adding a value of the logarithm-likelihood in the observation performed at the time t to a value of the logarithm-likelihood ratio in the observation performed up to the time t−1. Since this updating formula is repetitively calculated, the updating formula of the occupation probability p(mi) can be expressed by the sum total as expressed in the following formula (2).
                    [                  Numerical          ⁢                                          ⁢          Formula          ⁢                                          ⁢          2                ]                                                                      log          ⁢                                    p              ⁡                              (                                                                            m                      i                                        ❘                                          z                      1                                                        ,                  …                  ⁢                                                                          ,                                      z                    T                                                  )                                                    1              -                              p                ⁡                                  (                                                                                    m                        i                                            ❘                                              z                        1                                                              ,                    …                    ⁢                                                                                  ,                                          z                      T                                                        )                                                                    =                              ∑                          t              =              1                        T                    ⁢                                          ⁢                      log            ⁢                                          p                ⁡                                  (                                                            m                      i                                        ❘                                          z                      t                                                        )                                                            1                -                                  p                  ⁡                                      (                                                                  m                        i                                            ❘                                              z                        t                                                              )                                                                                                          (        2        )            
Since the above-mentioned formula (2) is calculated on the assumption that the observation is performed one time at intervals of the time t, also when a number of times of observation has been used as a parameter, the updating formula of the occupation probability p(mi) can be expressed by the similar formula. That is, assuming that the parameter of the number of times of observation is denoted by k and that the formula (1) is repetitively calculated also K times similarly when the observation has been performed K times, the updating formula of the occupation probability p(mi) can be expressed by the sum total as the following formula (3).
                    [                  Numerical          ⁢                                          ⁢          Formula          ⁢                                          ⁢          3                ]                                                                      log          ⁢                                    p              ⁡                              (                                                                            m                      i                                        ❘                                          z                      1                                                        ,                  …                  ⁢                                                                          ,                                      z                    K                                                  )                                                    1              -                              p                ⁡                                  (                                                                                    m                        i                                            ❘                                              z                        1                                                              ,                    …                    ⁢                                                                                  ,                                          z                      K                                                        )                                                                    =                              ∑                          k              =              1                        K                    ⁢                                          ⁢                      log            ⁢                                          p                ⁡                                  (                                                            m                      i                                        ❘                                          z                      k                                                        )                                                            1                -                                  p                  ⁡                                      (                                                                  m                        i                                            ❘                                              z                        k                                                              )                                                                                                          (        3        )            
The left side of the formula (3) is logarithmic odds of an occupation probability p(mi|z1, . . . , zk) which has been obtained until the observation has been performed K times in the grid i, that is, a logarithm-likelihood ratio in the observation which has been performed K times.
In addition, in the following Patent Document 1, a technique for perceiving and estimating the surrounding objects by using the occupancy grid map is disclosed. In the technique disclosed in Patent Document 1, estimation of a dynamic dead angle area formed by a moving object is performed on the basis a difference between a static dead angle area on the occupancy grid map and a current dead angle area which is based on a current detection position.